Current prior art visualization tools include Paraview for parallel remote visualization environments. Tecplot, Ensight are standard engineering data visualization tools. Paraview Catalyst provides in-situ visualization tools. CAD software can also be used to manage physical surface definitions.
Computational models of products or physical processes, their operation, and the associated environment are used by engineers in the design and analysis of products and in determining their operating characteristics. Desktop computers with Graphics Processing Units (GPUs) have enabled rapid visualization of 3D geometries associated with computational models. These computational models can include the device's associated operating environment. This can include, but is not limited to, showing fluid dynamics properties, eddy currents, and combustion specifics.
Two prior art techniques used in the field of visualization include “post-processing” and “in-situ” processing of computational geometries. “Post-processing” of computational geometries involves generating visualization output of a completed computer simulation. In one prior art method, the full computational model is loaded into memory where a user can navigate in 3D dimensional space to inspect quantities of interest. This approach demands larger and larger dedicated visualization computer clusters to keep pace with the current trend in computer simulation towards High Performance Computing (HPC). In these architectures, simulation is performed on a remote server utilizing many high performance computer processors.
The challenge with a “post-processing” technique is that the data for visualization is typically large, is located on a remote server, and does not easily fit on a desktop computer. For post-processing, the post-processing file needs to be transferred either locally or to a visualization cluster of servers. A large visualization data file needs to be generated in addition to native simulation data. These large datasets have to be loaded into the computer doing the visualization and run on a computer configured with specialized visualization software.
“In-situ” visualization responds to the above mentioned problems but also has limitations. In-situ visualization extracts visualization data during a simulation. This can require additional memory beyond memory required for the simulation. The drawback of “in-situ” visualization is the loss of user interactivity “post-processing” provides. Prior art in-situ visualization tools pre-specify, typically through text configuration files, the visualization data prior to simulation. Further, significant additional memory at runtime is required to process visualization data. Also, a full graphic rendering pipeline is required within the simulation code.
In light of the above discussion, there appears to be a need for an image-based visualization paradigm to address the coupled challenges of scalability and interactivity in the engineering design process with HPC. Further, what is needed is a system that provides a framework for a desktop computer, laptop, or tablet to interface over a network with a HPC system with an efficient method to transfer visualization information that preferably utilizes Web browser standard protocols for rendering views of the simulation. Additionally, what is needed is the ability for rapid and scalable visualization of temporal, spatially unstructured datasets, feature identification on complex 3D geometries, and quantitative surface data comparisons across computational models